Recursion

“This is a once-in-a-lifetime opportunity.” In a Fireside Chat with Recursion co-founder and CEO Chris Gibson at Download Day, NVIDIA founder and CEO Jensen Huang shared his vision for the future of healthcare, and how the companies are working together on a data-driven approach to drug discovery that has the potential to radically transform medicine.  ◾ Why he’s excited about this collaboration: “If you look at the foundation of Recursion, three things are in play – the invention of a new algorithm, a new family of algorithms that we call deep learning; supercomputing capabilities that you’ve used here and that we’ve partnered with you to create; and the know-how of processing and extracting the meaning of biology that’s embedded within life, within that data.” ◾ With accelerated computing and generative AI, we are changing “the type of problems we can solve,” he added. ◾ NVIDIA has been an incredible partner as we push to develop the next generation of medicines for patients in need -- including their support in building BioHive-2, the largest supercomputer in the pharma industry, which allows us to run more experiments, build more data, and develop even more powerful foundation models. Watch the full Fireside Chat here: https://lnkd.in/evqAm3QB The full day of presentations and slides from Download Day, featuring experts from across the Recursion ecosystem sharing the latest developments on our platform, pipeline and partnerships, is available here: https://lnkd.in/e9bRKvqf  #techbio #future #ai #health #medicine #pharma #tech

Unlocking a lifetime of genetic insights. A story by Brian K. Buntz in Drug Discovery & Development highlights our partnership with Helix in which we are combining Helix’s growing clinico-genomic dataset with more than 25 petabytes of our proprietary biological and chemical data. ◾ This genomic information about patients, he writes, provides "insights for years to come" and "can help unearth the hidden connections between genes, diseases, and potential treatments." ◾ The story notes that the partnership will utilize a "secret weapon" -- the BioHive-2 supercomputer -- "the fastest, wholly-owned supercomputer in the pharmaceutical industry globally." ◾ He writes: "Over the past decade, Recursion has also amassed one of the world’s largest collections of biological and chemical data. Now that its supercomputer, BioHive-2, is operational, it plans to use the horsepower to create more advanced AI models that can help streamline the drug discovery process." Read more: https://lnkd.in/eQtBYYfj #ai #drugdiscovery #data #techbio #supercomputer #biotech #pharma #patients

🎤 Speaker Announcement: Estefanía Barreto-Ojeda, PhD, ML Engineer at Recursion Join Estefania on her presentation on "Industrializing ML Workflows in Drug Discovery" where she'll share insights into Recursion's approach to predicting compound properties crucial for drug discovery using ML. 🌟 Session Highlights: - Overview of ML workflows for predicting compound properties like ADME and toxicity. - Strategies for managing large and diverse chemical assays datasets. - Deployment techniques using cloud and supercomputing resources. - Automation solutions to accelerate drug discovery processes. 👩💼 Estefania is an ML Engineer at Recursion Pharmaceuticals with a PhD in Biophysical Chemistry from the University of Calgary. She specializes in automating ML pipelines for drug discovery and has presented at major data conferences including PyData. 📅 Register Now: https://lnkd.in/g6EEsEc

The AI transformation of drug discovery is underway. A new story from Rachel Brazil in The Pharmaceutical Journal looks at how we are leveraging AI capabilities, computing power, and purpose-built data to identify novel biomarkers and targets, and accelerate the drug discovery pipeline end to end. ◾ She writes: "The pharmaceutical industry has been successfully using computers and mathematical models to identify and design new drugs for several decades, but the development of generative AI — based on deep neural networks and large language models capable of understanding and generating text — has brought big changes." ◾ In the article, Imran Haque describes how Recursion's approach involves collecting microscopy images from human cell assays, taking pictures to compare disease and healthy states, and feeding those images into trained AI models that identify 1,000 different features in each image. “This turns out to be an incredibly powerful capability,” he says. Read the full article: https://lnkd.in/gBSNG_at #ai #techbio #pharma #drugdiscovery #biotech #biopharma Pharmaceutical Journal Publications

A Seismic Shift in Drug Discovery⚕ I recently heard a talk from NVIDIA CEO Jensen Huang that made me realize – the tech transformation of pharma over the next decade may be one of the most seismic shifts we will see in any category. It’s an industry ripe for disruption. It takes 10+ years and costs billions of dollars to bring a drug to market – with over 90% of drugs failing in clinical trials. While tech has made other industries more efficient, drug discovery has become slower and more expensive over time. But now, the scale of data and compute in drug discovery is reaching an inflection point. “We understand biology,” NVIDIA CEO Jensen Huang said in conversation with Recursion CEO Chris Gibson, “but it’s so hard to understand interrelatedness. You need AI. You’re producing intelligence that leads to the production of drugs.” What does this mean? Scientists will no longer have to rely on physical lab experiments alone to unlock new insights – we can train AI models to make predictions that allow scientists to make more informed decisions about experiments to run and targets to go after.. Jensen said he once thought ray tracing – modeling light in 3-D graphics – would take decades to achieve with existing computing power. But they only had to simulate one pixel – AI could guess the other 64. In a similar way, he says “You don’t have to brute force simulate the physics for every single protein and every single cell.” This new category, TechBio, looks to turn drug discovery into a search problem where connected datasets train AI models to make accurate predictions. To achieve this, scalable, relatable, and reliable data are critical. For example, Recursion has spent years building its proprietary dataset – including images of billions of cells – amassing over 50 petabytes of biological, chemical and patient data. It’s one of the largest datasets of its kind in the world. Experiments and data collection happen in a highly automated wet lab nearly round the clock and this data is optimized to train AI models. (For context, the company does a PhD’s worth of lab work in about 15 minutes.)  The second part of the equation to analyze the data is compute power. Jensen said NVIDIA was “the first chip company to build supercomputers for our own use” while Tesla was the “first car company to build supercomputers.” Now, with NVIDIA, Recursion has built the largest supercomputer in pharma. https://lnkd.in/gtv9_3Dq A decade in, with compute, data, and foundation models, Recursion continues to industrialize across the drug discovery and development chain – getting to lead drugs 3x faster than industry average at 2.5X less cost. And this is only the beginning. Watch this space. #technology #innovation #biotech #pharma #drugdiscovery 

Drug discovery is now a technology industry. ◾ It used to be that supercomputers were only found in aerospace and engineering. Now, together with NVIDIA, we’ve built one of the top 35 supercomputers in the world – BioHive-2 – to digitize biological data at a resolution and scale that can rapidly accelerate new discoveries – and new medicines. ◾ Although demand for GPUs and supercomputers has been extremely high, we’re moving at “Recursion speed.” ◾ Together, we built BioHive-2 in less than three weeks. Learn more: https://lnkd.in/gW4A9Xgk #techbio #biopharma #biotech #pharma #ai #data #supercomputer #biology #downloadday

Working together to discover new therapies in oncology and neuroscience using phenomics, single-cell data generation, and AI and ML capabilities. ◾ In his presentation at Download Day, John Marioni, SVP and Head of Computational Sciences at Genentech shared Genentech’s “Lab in a Loop” vision to massively scale drug discovery into a “self-driving lab” – from experiment, to training, to prediction. ◾ As he described, Genentech is leveraging the Recursion operating system to find the right molecules that could result in transformative medicines in neuroscience or oncology. ◾ As part of this collaboration, we are developing maps in gastrointestinal cancer and neuroscience. ◾ The next steps include leveraging public data and integrating new and derived data into our models – driving a “virtuous cycle” of experimentation and machine learning. View all the Download Day presentations here: https://lnkd.in/e9bRKvqf Genentech #techbio #downloadday #ai #ml #drugdiscovery #oncology #neuroscience

Recursion is making a bold bet on supercomputing in drug discovery. In 2023, the company announced a strategic partnership with NVIDIA, that included a $50 million investment to support the development of novel foundation models for AI-enabled drug discovery. NVIDIA CEO Jensen Huang was recently highlighted at Recursion's Download Day event, where he urged Recursion and other similarly digitally savvy companies to embrace risk and a "once-in-a-lifetime opportunity." While a certain amount of risk is a given, companies must have the courage to venture into the unknown. As Huang put it, "You have to be willing to take that leap." Thanks to Olivia Bass for sharing the news.

“Looking beyond the lampposts, looking beyond the known biology, is what Recursion’s platform promises to unlock.” ◾ The Bayer-Recursion collaboration brings together Recursion’s technology-forward and AI-leading emphasis and Bayer’s legacy of drug development. The $1.5B deal announced last October in precision oncology already has one joint project now rapidly advancing to Lead Series nomination. ◾ We are on track to complete 25 unique multimodal data packages in Q3. ◾ The Recursion operating system allows Bayer to scale up data generation, explore a large number of oncology targets simultaneously, and “do unbiased discovery.” ◾ Announced at Download Day, Bayer will be the first beta-user of our LOWE LLM-orchestrated workflow software, which will be integrated across the collaboration and offer a more exploratory and intuitive research environment for scientists on both sides. #techbio #ai #platform #partnership #pharma #cancer #oncology #downloadday

The Recursion difference.  As Chris Gibson welcomed investors, analysts, and Recursionauts to Download Day, he provided a vision for the future of the Company and how it is poised to drive a new era of drug discovery. In short: it’s all about the data. ◾ “Everyone is using public datasets and making the same conclusions,” he said. “Data is our biggest differentiator.” ◾ Over the past decade Recursion has built massive, interconnected datasets, gained supercomputing capabilities, and developed ever-more-sophisticated foundational models. ◾ Experts both inside and outside the company shared how we are stitching these data layers together to unlock the vast unknown biological space – discovering novel targets for disease and designing new medicines for patients – with 7 of these clinical programs expected to have readouts in the next 18 months.    ◾ As Laura Schaevitz said: “We’ve already identified thousands of program ideas, validated hundreds through industrialized experiments, resulting in dozens of exciting program opportunities, many with strong chemical matter at the start.” ◾ We heard from our partners at Bayer – who we announced will be the first beta users of our LLM tool LOWE – as well as John Marioni at Genentech who talked about the transformational moment we face and how important it is to build a Bilingual Culture – with computational and basic scientists who speak the same language and are fully engaged across disciplines. ◾ And of course, we were thrilled to welcome Jensen Huang in a closing Fireside Chat. NVIDIA has been a critical partner as we build the TechBio company of the future with the computing power to truly transform the industry. Watch the Download Day presentations and check out the slides here: https://lnkd.in/e9bRKvqf Thank you to everyone who joined us and made the day such a success! Lina Nilsson Imran Haque David Mauro Najat Khan, PhD Michael Secora PhD Matthew Kinn Deepak Nijhawan Ryan Kelly Berton Earnshaw Daniel Cohen Hayley Donnella #techbio #downloadday #partners #future #healthcare #tech #pharma